tbuckley/cabot-search huggingface dataset:
Abstract 1620: Clonal hematopoiesis of indeterminate potential in the companion dog
Authors: Kimberley N. Sebastian, Hatice Gülçin Özer, Cory Howard, Laura Chadsey, Arletta Lozanski, Tzyy-Jye Doong, Gerard Lozanski, Wenjuan Ma, William C. Kisseberth, John C. Byrd, Bonnie K. Harrington
Journal: Cancer Research (2022)

Abstract Background: Clonal hematopoiesis of indeterminate potential (CHIP) is a clinical entity of aging humans that is characterized by cancer-associated mutations in white blood cells, without evidence of overt neoplasia. CHIP has been associated with an increased risk of hematologic cancers, cardiovascular disease, and all-cause mortality. We hypothesized that somatic mutations in specific genes associated with human CHIP would be detectable in the blood of aged dogs not known to have hematologic disorders. Methods: DNA from paired germline and whole blood samples from 93 geriatric canine patients affected by solid cancer were subjected to targeted next generation sequencing. Impact of the variants was predicted using Polymorphism Phenotyping version 2 software (PolyPhen-2, Harvard). Clinical and demographic data were extracted from medical records. Results: Somatic variants were detected in peripheral blood of four (4.3%) female dogs aged 12-15 years. Affected genes were ASXL1, KIT, SF3B1, TET2, RUNX1, and PPM1D. The variant in PPM1D was a nonsense mutation, while the other five variants were single nucleotide non-synonymous variants in protein coding regions of the genes. Following analysis by PolyPhen-2, the single nucleotide variants in KIT and SF3B1 were predicted to be benign, while the variants in ASXL1, TET2, and RUNX1 were predicted to be damaging. Conclusion: These results support the presence of variants in CHIP-associated genes in geriatric canids at a frequency similar to that observed in people, and the dog represents the first species in which the genetic lesion of CHIP has been documented. Further investigations are needed to confirm the association of this genetic lesion with clinical outcomes. Citation Format: Kimberley N. Sebastian, Hatice Gülçin Özer, Cory Howard, Laura Chadsey, Arletta Lozanski, Tzyy-Jye Doong, Gerard Lozanski, Wenjuan Ma, William C. Kisseberth, John C. Byrd, Bonnie K. Harrington. Clonal hematopoiesis of indeterminate potential in the companion dog [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1620.
Abstract 6109: Clonal relationship of B cells between tertiary lymphoid structures (TLSs) and tumor infiltrating lymphocytes (TILs) in advanced endometrial cancer
Authors: Haruka Suzuki, Junzo Hamanishi, Meng Qin, Masayo Ukita, Akihiko Ueda, Shunsuke Kawahara, Koji Yamanoi, Taito Miyamoto, Shiro Takamatsu, Mana Taki, Yoko Hosoe, Takashi Kobayashi, Ken Yamaguchi, Masaki Mandai
Journal: Cancer Research (2022)

Abstract Objective: Tertiary lymphoid structures (TLSs) are known to be a marker of peripheral inflammation. While high densities of TLSs were reported to be associated with longer patient survival in several cancer types, there is no direct evidence where B cells in TLSs(TLBs) are derived from and whether these clones are consistent with tumor infiltrating B cells (TIBs), in endometrial cancer. Methods: We analyzed the pathological distribution of TLSs and TIBs in human endometrial cancer samples using immunohistochemistry of a series of B cell markers and evaluated the relationship with patients’ clinical outcomes. Additionally, we micro-dissected six pairs of tumor nests and their neighbor TLSs and analyzed the clonal consistency between TLBs and TIBs using the sequencing of complementarity-determining region (CDR) of B cell receptor (BCR). Results: In 104 patients with endometrial cancer, TLSs were detected in 81 patients (78%), and the absence of TLS was related to worse progression-free survival (PFS) (HR, 0.15, P &amp;lt;0.01). Among TLS-detected cases, the high number of TIBs was significantly associated with better PFS (P&amp;lt;0.05). BCR analyses in the six patients found that three patients with advanced stage had a unique B cell clones in common between TLBs and TIBs, while the other three patients with early stage did not have any common B cell clones. The frequency of common B cell clones in the former three patients were 10.3% (5250/51146 reads), 9.7% (1873/19369 reads) and 3.0% (1034/34618 reads). Conclusion: TLSs and TIBs are associated with better prognosis in endometrial cancer. Common B cell clones were found in the advanced stage cases, suggesting that B cells may have gradually acquired immunospecificity in TLSs. Citation Format: Haruka Suzuki, Junzo Hamanishi, Meng Qin, Masayo Ukita, Akihiko Ueda, Shunsuke Kawahara, Koji Yamanoi, Taito Miyamoto, Shiro Takamatsu, Mana Taki, Yoko Hosoe, Takashi Kobayashi, Ken Yamaguchi, Masaki Mandai. Clonal relationship of B cells between tertiary lymphoid structures (TLSs) and tumor infiltrating lymphocytes (TILs) in advanced endometrial cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6109.
Abstract 3408: Longitudinal measurement of HPV copy number in cell free DNA predicts progression free survival in HPV positive oropharyngeal cancer
Authors: Martyna Joanna Adamowicz, Sophie J. Warlow, John P. Thomson, Lara M. Carey, Helen Thain, Robert Wescott, Kate Cuschieri, Lucy Q. Li, Brendan Conn, Ashley Hay, Iain J. Nixon, Timothy J. Aitman
Journal: Cancer Research (2022)

Abstract Oropharyngeal squamous cell carcinoma (OPSCC) is increasing in global prevalence and is divided into two types dependent on association with human papillomavirus (HPV), with a more favorable prognosis in HPV+ve tumors. Assay of HPV copy number in plasma cell-free DNA (cfDNA) provides a minimally invasive method for detecting and monitoring tumor-derived HPV, with potential for enhancing clinical care. We have evaluated the utility of cfDNA droplet digital PCR (ddPCR) as a method for characterisation and longitudinal monitoring of patients with OPSCC in a prospectively recruited cohort of 104 OPSCC patients. ddPCR assay of cfDNA for five HPV types showed overall 95% concordance with p16 immunohistochemistry (IHC) and PCR analysis of solid tumor tissue. Longitudinal sampling in 48 HPV+ve patients, with median follow-up of 20 months, strongly predicted patient outcomes. Progression-free survival, stratified respectively by the presence or absence of detectable HPV cfDNA at a median of 13 weeks post-treatment, was 50% and 88% (p=0.001, hazard ratio 10.0 (95% CI 2.1-47.1)). In two patients, greater reliance on sequential HPV measurement would have avoided surgical intervention which ultimately did not confirm disease recurrence. The high concordance of pre-treatment plasma cfDNA-HPV analysis with p16 IHC and HPV-PCR of solid tissue, together with the predictive value and utility of sequentially measured post-treatment cfDNA-HPV copy number, provide a compelling case for the routine use of cfDNA-HPV ddPCR in management of OPSCC and for clinical trials to assess its impact on treatment outcomes. Citation Format: Martyna Joanna Adamowicz, Sophie J. Warlow, John P. Thomson, Lara M. Carey, Helen Thain, Robert Wescott, Kate Cuschieri, Lucy Q. Li, Brendan Conn, Ashley Hay, Iain J. Nixon, Timothy J. Aitman. Longitudinal measurement of HPV copy number in cell free DNA predicts progression free survival in HPV positive oropharyngeal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3408.
Abstract 2698: ERα and NAMPT crosstalk at enhancers drives Fulvestrant resistance in metastatic breast tumors
Authors: Ayca N. Mogol, Christine Chien, Qianying Zuo, Akshara S. Raghavendra, Debu Tripathy, Yosef Landesman, Zeynep Madak Erdogan
Journal: Cancer Research (2022)

Abstract Approximately 70% of human breast cancers express estrogen receptor alpha (ERα), providing a potential for targeted endocrine therapy for patients. Unfortunately, 30-40% of ER+ patients still experience recurrence and metastasis, with a 5-year relative overall survival rate of just 24% for patients with metastatic disease. Previously, we described an increased reliance on NAD+ metabolism in metastatic breast cancer (MBC) cells, which are driven by clonal selection from monotherapy resistance and the metastatic organ microenvironment. In the current study, we investigated if inhibition of NAMPT to block NAD+ production would synergize with standard of care therapies for ER+ MBC. Combination therapy of the NAMPT Inhibitor, KPT9274 and the ERα agonist Fulvestrant (Fulv) synergistically reduced tumor burden in liver metastasis in vitro (combination index &amp;lt; 1 in cell viability assays) and in vivo in mouse xenograft models. A synergistic effect was not observed when KPT-9274 was combined with Palbociclib or Tamoxifen, nor Fulv with other metabolic inhibitors. RNA-Seq analysis showed that NAMPT inhibition restored antiestrogenic activity of Fulv. Metabolomics analysis showed that NAMPT inhibition reduced abundance of metabolites associated with glucose and lipid metabolism. Mechanistically, chromatin immunoprecipitation showed that NAMPT is recruited to ERα binding sites in MBC xenografts and PDX tumors. Targeting metabolic adaptations in endocrine-resistant metastatic breast tumors is a novel approach that could lead to new combined therapies that reduce mortality. Citation Format: Ayca N. Mogol, Christine Chien, Qianying Zuo, Akshara S. Raghavendra, Debu Tripathy, Yosef Landesman, Zeynep Madak Erdogan. ERα and NAMPT crosstalk at enhancers drives Fulvestrant resistance in metastatic breast tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2698.
Abstract 1932: Pollock: Fishing for cell states
Authors: Erik Storrs, Daniel Cui Zhou, Michael C. Wendl, Matthew A. Wyczalkowski, Alla Karpova, Liang-Bo Wang, Yize Li, Austin Southard-Smith, Reyka G. Jayasinghe, Lijun Yao, Ruiyang Liu, Yige Wu, Nadezhda V. Terekhanova, Houxiang Zhu, John M. Herndon, Feng Chen, William E. Gillanders, Ryan C. Fields, Li Ding
Journal: Cancer Research (2022)

Abstract The use of single-cell methods is expanding at an ever-increasing rate. While multiple algorithms address the task of cell classification, they are limited in terms of cross platform compatibility, reliance on the availability of a reference dataset, and classification interpretability. Here, we introduce Pollock, a suite of algorithms for cell type identification that is compatible with popular single cell methods and analysis platforms, provides a series of pretrained human cancer reference models, and reports interpretability scores that identify the genes that drive cell type classifications. Our model combines two important approaches, one each from machine learning and deep learning: a variational autoencoder (VAE) and random forest classifier, to make cell type predictions. Pollock is highly versatile, being available as a command line tool, Python library (with scanpy integration), or R library (with Seurat integration), and can be installed as a conda package, or in containerized form via Docker. To allow for easier pan-disease and pan-tissue analyses, Pollock also ships with a library of pretrained cancer type specific and agnostic modules that were trained on expertly-curated single cell data that are ready to “plug and play” with no additional annotation or training required. Conversely, Pollock also allows for the training of custom classification modules, if an annotated reference single cell dataset is available. These pretrained models were fitted on manually curated and annotated single cell data from eight different cancer types spanning three single cell technologies (scRNA-seq, snRNA-seq, and snATAC-seq). Pollock also provides feature importance scores that allow for cell type classifications to be traced back to the genes influencing a particular cell type classification, further promoting biological interpretability. These scores could allow for new, technology-specific biomarker discovery. We also demonstrate the utility of Pollock by applying it in a pan-cancer single cell immune analysis. Citation Format: Erik Storrs, Daniel Cui Zhou, Michael C. Wendl, Matthew A. Wyczalkowski, Alla Karpova, Liang-Bo Wang, Yize Li, Austin Southard-Smith, Reyka G. Jayasinghe, Lijun Yao, Ruiyang Liu, Yige Wu, Nadezhda V. Terekhanova, Houxiang Zhu, John M. Herndon, Feng Chen, William E. Gillanders, Ryan C. Fields, Li Ding. Pollock: Fishing for cell states [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1932.
Abstract 600: Discovery of a single-domain antibody fragment targeting PD-L1 for cancer immunotherapy
Authors: Yanli Liu, Hao Liu, Kun Cheng
Journal: Cancer Research (2022)

Abstract Immunotherapy has shown enormous promise for cancer treatment. The use of Antibodies to target immune checkpoints, particularly PD-1/PD-L1, has made a profound impact in cancer immunotherapy. Single-domain antibody fragment (sdAb) is an antibody fragment composed of a single variable domain of the heavy chain. sdAb is the smallest antibody fragment (15 kDa) that maintains the similar antigen-binding affinity. sdAbs show many advantages over monoclonal antibodies such as small size, low immunogenicity, ease of production, and ease of modification, making sdAbs promising candidates for cancer immunotherapy. Here, we use a phage display library to identify an anti-PD-L1 sdAb (CLV3) which effectively blocks the PD-1/PD-L1 interaction. The CLV3 sdAb demonstrates high binding affinity and specificity to PD-L1 protein and PD-L1 overexpression DU145 tumor cells. Moreover, the CLV3 sdAb exhibits efficient tumor penetration in a 3D tumor spheroid model, suggesting its good penetration capability in the tumor microenvironment in vivo. CLV3 restores T cell proliferation and reduces T cell apoptosis in the co-culture experiment of peripheral blood mononuclear cells (PBMC) with tumor cells. These data suggest that the CLV3 sdAb can be potentially used as an anti-PD-L1 inhibitor for cancer immunotherapy. Citation Format: Yanli Liu, Hao Liu, Kun Cheng. Discovery of a single-domain antibody fragment targeting PD-L1 for cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 600.
Abstract 1220: Accurately genotyping HLA and KIR alleles using cfDNA assay and k-mer based algorithm for immunotherapy
Authors: Sante Gnerre, Brian Yik Tak Tsui, Tingting Jiang, Yvonne Kim, Dustin Ma, Indira Wu, Rebecca Nagy, Han-Yu Chuang
Journal: Cancer Research (2022)

Abstract Background: HLA and KIR genotypes show great promise as emerging biomarkers for immune checkpoint inhibitors (ICIs) and understanding patient prognosis. Multiple studies have shown that HLA-I heterozygosity and high sequence divergence across alleles positively correlates with response to ICIs. However the high degree of polymorphism and allele sequence similarities in HLA and KIR present a challenge to accurate allele calling. To address these difficulties we developed kmerizer, a novel allele caller optimized for short fragments, such as reads from a cfDNA assay. Methods: We tested kmerizer on MHC class1 and class2 genes, and on KIR genes, on both simulated datasets and real samples (cell lines and plasma samples). To assess the capability of the algorithm to distinguish highly homologous allele pairs, we simulated cfDNA-like fragments with errors on randomly selected allele pairs, and on allele pairs with a high level of homology. Twelve plasma samples and 19 reference cell lines fragmented to cfDNA size were analyzed using a NGS cfDNA assay. For plasma samples, paired buffy coats were sent to an external vendor for HLA typing using multiplex PCR-based amplicon and sequenced by 300bp paired-end reads. Results: Of the 19 cell lines and 12 plasma samples for HLA typing (A, B, C, and DQB1 loci), kmerizer delivered 100% sensitivity with 98% specificity. On the simulated dataset, kmerizer achieved 99% sensitivity and specificity on all the MHC class1 and class 2 loci, and 90% sensitivity and specificity on all KIR loci, for both homozygous and heterozygous pairs. The novel allele caller kmerizer also demonstrated a lighter footprint on computational resource need: one deep-sequencing plasma sample on average can be processed in less than 2 minutes which is about 15 times faster than the most commonly used HLA typing tool HISAT21, which does not support KIR typing. Conclusions: As utilization of ICIs increases, the use of genetic and genomic information to accurately identify patients more likely to respond to ICIs will be critical. kmerizer is a fast and highly sensitive and specific allele caller, and it can effectively call alleles on both HLA and KIR. References: [1] Kim, D., Paggi, J. M., Park, C., Bennett, C., &amp; Salzberg, S. L. (2019). Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nature biotechnology, 37(8), 907-915. Citation Format: Sante Gnerre, Brian Yik Tak Tsui, Tingting Jiang, Yvonne Kim, Dustin Ma, Indira Wu, Rebecca Nagy, Han-Yu Chuang. Accurately genotyping HLA and KIR alleles using cfDNA assay and k-mer based algorithm for immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1220.
Abstract 1931: Multi-cancer classification: An analysis of neural network complexity
Authors: James W. Webber, Kevin M. Elias
Journal: Cancer Research (2022)

Abstract Background: Often, in analysis of expression data, binary classification problems are considered, with the aim to separate a control group from a single cancer group (e.g., ovarian cancer). Such models lack any cancer specific information, as they are only trained on one cancer type. It is more useful and efficient to train a model on multiple cancer types, and controls, simultaneously, so that a physician can be directed to the correct area of the body for further testing. Results: We introduce novel, data-driven neural network models to address the multi-cancer classification problem across a number of data types commonly applied in cancer prediction, including circulating miRNA expression (blood draw), protein (tissue sample), and mRNA (tissue sample). In particular, we present an analysis of neural network depth and complexity and investigate how this relates to classification performance. Comparisons of our models are also given to the state-of-the-art neural network models from the literature. The proposed models yield high accuracy (mean AUC greater than 0.95) across all data types considered and are shown to offer greater performance when compared to the models from the literature. Conclusion: We have introduced a simple neural network framework which can be applied to multiple data types and which yields the best performance when compared to similar models from the literature. Upon analysis of the neural network complexity, we discover that shallow, feed-forward neural net architectures offer greater performance when compared to more complex deep feed-forward, Convolutional Neural Network (CNN), and Graph CNN (GCNN) architectures considered in the literature. The depth analysis indicates that shallow neural nets (e.g., 1 or 2 layers) are more favorable for this problem, when compared to deep architectures (e.g., more than 3 layers). The results show that multiple cancers and controls can be classified simultaneously, and accurately using the proposed models, across a range of expression technologies in cancer prediction. Citation Format: James W. Webber, Kevin M. Elias. Multi-cancer classification: An analysis of neural network complexity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1931.
Abstract 329: Understanding the role of GPR30 in the estrogen non-genomic signaling in inflammatory breast cancer
Authors: Xavier S. Bittman Soto, Adrian J. Rivera Lopez, Esther A. Peterson
Journal: Cancer Research (2022)

Abstract Inflammatory Breast Cancer (IBC) is rare and the most aggressive subtype of all breast cancers, reporting rapid progression, poor prognosis, and a unique clinical diagnosis (blockage of lymph vessels by tumor emboli). Approximately, 40% of IBC cases are classified as triple-negative breast cancer (TNBC), meaning they test negative for hormone receptors (estrogen and progesterone) and the amplification of the epidermal growth factor receptor 2 (HER2), which leads to no effective targeted therapies availability. However, 17β-estrogen (E2) has been found to enhance the migration and invasion phenotypes of TN-IBC cells and it has been associated with the presence of a membrane G-protein coupled estrogen receptor (GPR30) and a novel cytoplasmic estrogen receptor (ERα36 isoform) that can undergo an estrogen non-genomic (rapid) cell’s response. Recent studies have also reported a crosstalk between these estrogen non-genomic receptors and the epidermal growth factor receptor (EGFR) signaling pathway in the presence of E2, inducing phosphorylation of the extracellular signal-regulated kinase (ERK1/2) and promoting oncogenic phenotypes (migration &amp; invasion) in TN-IBC cells. However, the exact role of GPR30 and ERα36 in the non-genomic signaling pathway remains elusive in TN-IBC. We hypothesis that GPR30 and ERα36 are necessary to undergo de estrogen non-genomic signaling and promote oncogenic phenotypes in TN-IBC SUM149 cells after E2 treatment. Methods: We have measured migratory activity and tumor emboli formation of SUM149 cells (by wound-healing and 3D-cell proliferation assay), and phosphorylation levels of ERK1/2 and AKT kinases (by western-blot) after treatments in time-points with E2 alone and in combination with G15 (GPR30 antagonist drug). We are also working to identify protein partners of GPR30 (by Ip and Mass-spec) after E2 treatment, including physical interaction with ERα36, in TN-IBC and other types of breast cancers. Results: G15 treatment in Sum149 cells significantly reduced E2-induced ERK1/2 phosphorylation, indicating that GPR30 is necessary for the estrogen non-genomic signaling pathway and has direct involvement with the EGFR signaling cascade. Data acquired from these experiments will contribute to a better understanding of TN-IBC’s molecular structure and create new opportunities to develop novel targeted therapies. Citation Format: Xavier S. Bittman Soto, Adrian J. Rivera Lopez, Esther A. Peterson. Understanding the role of GPR30 in the estrogen non-genomic signaling in inflammatory breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 329.